Barrier Coverage Research Articles

Quasi-Monostatic Versus Near Forward Scatter Geometry in WiFi-Based Passive Radar Sensors

In this paper, the comparison is investigated between quasi-monostatic and near forward scatter configurations for WiFi-based passive radar sensors. To this purpose, a barrier coverage application for vehicular targets is considered as a possible implementation of the conceived green sensor within surface transportation monitoring solutions. The performance of the two alternative sensor geometries are compared by means of theoretical and experimental analysis as well as based on considerations on the practical implementation. The reported results provide a realistic characterization of the performance of a bistatic radar sensor to be exploited in barrier coverage problems and give indications for the design of such a system. The specific demonstration with WiFi-based passive radar aims at extending the use of this emerging technology to perimeter monitoring applications for vehicular targets, exploiting the near forward scatter geometry.

Cost-effective barrier coverage formation in heterogeneous wireless sensor networks

Barrier coverage is a critical issue in wireless sensor networks (WSNs) for security applications, which however cannot be guaranteed to be formed after initial random deployment of sensors. Existing work on barrier coverage mainly focus on homogeneous WSNs, while little effort has been made on exploiting barrier coverage formation in heterogeneous WSNs where different types of sensors are deployed with different sensing models and costs. In this paper, we study how to efficiently form barrier coverage by leveraging multiple types of mobile sensors to fill in gaps between pre-deployed stationary sensors in heterogeneous WSNs. The stationary sensors are grouped into clusters and a cluster-based directional barrier graph is proposed to model the barrier coverage formation problem. We prove that the minimum cost of mobile sensors required to form a barrier with stationary sensors is the length of the shortest path on the graph. Moreover, we propose a greedy movement algorithm for heterogeneous WSNs to efficiently schedule different types of mobile sensors to different gaps while minimizing the total moving cost. In particular, we formulate the movement problem for homogeneous WSNs as a minimum cost bipartite assignment problem, and solve it in polynomial time using the Hungarian algorithm. Extensively experimental results on homogeneous and heterogeneous WSNs demonstrate the effectiveness of the proposed algorithms.

In Vitro Assays to Assess Blood-brain Barrier Mesh-like Vessel Formation and Disruption.

Blood-brain barrier (BBB) coverage plays a central role in the homeostasis of the central nervous system (CNS). The BBB is dynamically maintained by astrocytes, pericytes and brain endothelial cells (BECs). Here, we detail methods to assess BBB coverage using single cultures of immortalized human BECs, single cultures of primary mouse BECs, and a humanized triple culture model (BECs, astrocytes and pericytes) of the BBB. To highlight the applicability of the assays to disease states, we describe the effect of oligomeric amyloid-β (oAβ), which is an important contributor to Alzheimer's disease (AD) progression, on BBB coverage. Further, we utilize the epidermal growth factor (EGF) to illuminate the drug screening potential of the techniques. Our results show that single and triple cultured BECs form meshwork-like structures under basal conditions, and that oAβ disrupts this cell meshwork formation and degenerates the preformed mesh structures, but EGF blocks this disruption. Thus, the techniques described are important for dissecting fundamental and disease-relevant processes that modulate BBB coverage.

Minimum Perimeter Coverage Set Based on Points of Tangency and Strong Barrier for an Extended WSN Lifetime

The random deployment of sensors in the area of interest triggers several research issues. Among them, we can cite connectivity, localization and coverage. In this paper, we focus on the latter one. Our objective is to monitor the perimeter of a region of interest with circular shape from intrusions. We propose a new approach to define the minimum coverage set based on points of tangency and strong barrier coverage. Furthermore, in order to exploit the redundancy of information due to the random deployment of nodes, we also suggest a new approach to generate the scheduling sets, which consists on the creation of multiple virtual perimeters around the area of interest, upon which the minimum coverage sets is constructed. In other words, the objective is to minimize the number of nodes in coverage set and to maximize the number of coverage sets for scheduling. These disjoint sets of sensors can be activated one after the other to further extend the network lifetime or multiple sets at time and reach k-barrier coverage for strong surveillance applications. Simulation results show that to generate the minimum coverage set, our approach gives better results compared to those proposed in the literature. Moreover, the approach of constructing the scheduling sets significantly increases the network lifetime.

Rotating Directional Sensors to Mend Barrier Gaps in a Line-Based Deployed Directional Sensor Network

The barrier coverage of a wireless sensor network is an important surveillance application of Internet of Things. Barrier coverage guarantees that all intruders traversing the protected region are detected by a chain of connected sensors. However, when the sensors are randomly deployed, barrier gaps may occur due to deployment randomness or insufficient sensors. How to locate the barrier gaps and mend them is an important aspect in the network. In this paper, we study the barrier gap problem in weak barrier coverage and strong barrier coverage that consist of directional sensors, and the sensors are deployed by a line-based deployment strategy. A gap-finding algorithm is proposed to find subbarriers and barrier gaps. Two gap-mending algorithms are devised to mend barrier gaps in the network: One algorithm is a simple rotation algorithm that only rotates two critical sensors in two subbarriers to fix the gap, and the other algorithm is a chain-reaction rotation algorithm that rotates sensors in the subbarrier in a chain-reaction manner to mend the gap. We conduct extensive simulations to evaluate the performance of the proposed algorithms. Simulation results show that the proposed gap-mending algorithms can effectively fix barrier gaps and improve the probability of barrier success construction.

A Probabilistic Barrier Coverage Model and Effective Construction Scheme

A Probabilistic Barrier Coverage Model and Effective Construction Scheme

Barrier coverage of WSNs with the imperialist competitive algorithm

Barrier coverage in wireless sensor networks has been used in many applications such as intrusion detection and border surveillance. Barrier coverage is used to monitor the network borders to prevent intruders from penetrating the network. In these applications, it is critical to find optimal number of sensor nodes to prolong the network lifetime. Also, increasing the network lifetime is one of the important challenges in these networks. Various algorithms have been proposed to extend the network lifetime while guaranteeing barrier coverage requirements. In this paper, we use the imperialist competitive algorithm (ICA) for selecting sensor nodes to do barrier coverage monitoring operations called ICABC. The main objective of this work is to improve the network lifetime in a deployed network. To investigate the performance of ICABC, several simulations were conducted and the results of the experiments show that the ICABC significantly improves the performance than other state-of-art methods.

Analyzing and shaping the lifetime and the performance of barrier coverage sensor networks

In this work we model and provide the means to extend the lifetime of a barrier coverage sensor network deployed fortarget detection. We consider a scenario where sensors are randomly dropped on a bidimensional field in order to detect target traversals which occur in a stochastic way within a critical mission time. Once a target enters a sensor's detection area, the sensor transmits such information to a cluster head, in charge of receiving and retransmitting the messages received from the sensors deployed on the field. The contribution of this work is fourfold. We first identify the sensing nodes whose behavior is key to model the duration of sensing operations, assuming prior arrival and mobility models for target traversals. We then proceed, providing a heuristic estimation of the traffic received by the cluster head to quantify its energy requirements, resorting to specific lifetime definitions. We also evaluate the relationship between our probabilistic and heuristic models and the time until the barrier remains capable of detecting and reporting the traversal of any target to a sink, as obtained by simulation. Finally, we show how the lifetime of such network may be shaped, with the use of a sequential activation mechanism, for example to combat the traversals of adversaries exploiting the lifetime models obtained in this work.

Optimizing Detection Quality and Transmission Quality of Barrier Coverage in Heterogeneous Wireless Sensor Networks

This paper proposes an algorithm, called the Optimized Barrier Coverage Algorithm (OBCA), to optimize the quality of the barrier coverage formed by a wireless sensor network (WSN). OBCA aims at optimizing the barrier coverage quality in terms of the detection degree, the detection quality, and the transmission quality (i.e., the expected transmission time). This paper also proposes a model to formulate the minimum detection probability between two WSN sensors with different sensing ranges. With the model, OBCA can be applied to heterogeneous WSNs whose sensors have various sensing ranges. OBCA’s optimization is proved, and its time complexity is analyzed. The performance of OBCA is simulated and compared with those of two related algorithms.

Energy-Efficient Probabilistic Barrier Construction in Directional Sensor Networks

${k}$ -barrier coverage is one of the critical issues in directional sensor networks. In actual application, the sensing distance becomes small with the increase of sensing angle, and the event sensing probability is constantly changing as the distance between node and event changes. But so far, there is no high efficient distributed barrier construction scheme based on a directional probabilistic sensing model. This paper first creates a directional probabilistic sensing model with changing angle, based on which four target locations of barrier member are created in a distributed manner. In addition, the energy efficiency ratio (EER) is investigated to minimize the energy consumption. Based on these two models, a distributed probabilistic barrier construction scheme based on EER is proposed, which commences the initiator of the barrier on the west end boundary and selects suitable relay sensors from left to right until the east end boundary is reached. The target locations and corresponding orientations of barrier member are determined only by its ancestor. When there are many candidate relay sensors, the one with the largest EER is the actual relay sensor. Simulation results indicate our method could form ${k}$ -barrier coverage with smaller energy consumption than other methods.

Activities scheduling algorithms based on probabilistic coverage models for wireless sensor networks

Area monitoring using Internet and barrier coverage is a typical application of wireless sensor networks. The main concerns in this type of applications are coverage efficiency and sensor energy conservation. For that, many activities scheduling algorithms are proposed in the literature. Unlike prior efforts based on an unrealistic binary sensor coverage model, this paper proposes three efficient activities scheduling algorithms based on realistic sensor coverage models. The first algorithm (C1L-PBC) is centralized and it is based on a coverage graph. The second algorithm (D1L-PBC) is distributed and it ensures 1-barrier coverage; whereas, the third one (D2L-PBC) is also distributed and it guarantees 2-barrier coverage. The obtained experimental results show that the proposed algorithms can effectively guarantee the barrier coverage and prolong the sensor network lifetime.

Maximizing Barrier Coverage Lifetime with Mobile Sensors

Sensor networks are ubiquitously used for detection and tracking and, as a result, covering is one of the main tasks of such networks. We study the problem of maximizing the coverage lifetime of a barrier by mobile sensors with limited battery power, where the coverage lifetime is the time until there is a breakdown in coverage due to the death of a sensor. Sensors are first deployed and then coverage commences. Energy is consumed in proportion to the distance traveled for mobility, while for coverage, energy is consumed in direct proportion to the radius of the sensor raised to a constant exponent. We study two variants which are distinguished by whether the sensing radii are given as part of the input or can be optimized: the fixed radii problem and the variable radii problem. We design parametric search algorithms for both problems for the case where the final order of the sensors is predetermined (e.g., sensors cannot swap locations and the initial order must be preserved) and for the case where senso...

Compound Event Barrier Coverage Algorithm Based on Environment Pareto Dominated Selection Strategy in Multi-Constraints Sensor Networks

There are a variety of complex constraints in the wide application of wireless sensor networks. Traditional coverage models and algorithms have been unable to meet the needs of multi-constrained sensor networks. At the same time, in a complex monitoring environment, a single type of sensor information cannot meet the requirements of reliable monitoring. Hence, in this paper, aiming at the multi-constraints in sensor networks, a compound event barrier coverage algorithm is proposed based on environment Pareto-dominated selection strategy, which can distribute the sensor resources reasonably and find out the coverage ratio efficiently in multi-constraints sensor networks. The proposed algorithm takes advantage of Pareto domination relationship, constraint violation degree, constraint boundary distance, and crowding degree to preserve the outstanding infeasible individuals in the evolutionary process and participate in the mutation operation; we also adopt the adaptive scaling factor and crossover probability strategy to avoid the algorithm into local optimal. The proposed algorithm is proved to be more highly efficient than the latest algorithm in the distribution of sensor resources by experimental results.

Critical Density in Adjustable-Orientation Directional Sensor Networks Using Continuum Percolation

In this paper, we consider adjustable-orientation directional sensor networks (ADODSNs) in which nodes are deployed based on Poisson Point Process and the orientation of sensor nodes is distributed between 0 and 2π independently and uniformly. Despite of other kinds of directional sensor networks, orientation of sensor nodes in ADODSNS could be adjusted after deployment by using an algorithm. We call this kind of sensor networks, adjustable-orientation directional sensor networks. We calculate the critical density of nodes for both sensing coverage and network connectivity in such networks using continuum percolation where field-of-view angles of sensors could be between 0 and π. Critical density is the infimum density of nodes to prepare barrier coverage. Also, extensive simulations have been conducted to represent the results. The findings of this research could be used for offline design of directional sensor networks and also its online algorithms such as scheduling, coverage and tracking.

Compound Event Barrier Coverage in Wireless Sensor Networks under Multi-Constraint Conditions.

It is important to monitor compound event by barrier coverage issues in wireless sensor networks (WSNs). Compound event barrier coverage (CEBC) is a novel coverage problem. Unlike traditional ones, the data of compound event barrier coverage comes from different types of sensors. It will be subject to multiple constraints under complex conditions in real-world applications. The main objective of this paper is to design an efficient algorithm for complex conditions that can combine the compound event confidence. Moreover, a multiplier method based on an active-set strategy (ASMP) is proposed to optimize the multiple constraints in compound event barrier coverage. The algorithm can calculate the coverage ratio efficiently and allocate the sensor resources reasonably in compound event barrier coverage. The proposed algorithm can simplify complex problems to reduce the computational load of the network and improve the network efficiency. The simulation results demonstrate that the proposed algorithm is more effective and efficient than existing methods, especially in the allocation of sensor resources.

A decentralized K-barriers construction approach based on nearest neighbors rule for two-dimensional rectangular region

Barrier coverage is a fundamental problem in wireless sensor networks, which can be applied to detect intruders that attempt to cross the boundaries of the region we are supervising. Among a number of issues related to barrier coverage, the most critical one is how to deploy sensors to construct barriers. Many barrier-building approaches have been proposed in previous papers by other scholars, while few papers adopt distributed strategies which allow sensors to move autonomously based on local information and are more practical in some unreachable areas. In this paper, we study a decentralized approach based on the nearest neighbor rule (NNR) to realize the self-deployment of wireless sensor networks to build K strong barriers, while considering network connectivity. This approach can be divided into three stages which correspond to the three times of using the NNR respectively. The sensor can autonomously choose the closest barrier to belonging to, which ensures the total migration distance is relatively smallest. Moreover, we test the availability and performance of our approach with simulations.

Barrier coverage in energy harvesting sensor networks

Wireless Sensor Networks (WSNs) can be used effectively to form barriers that monitor strips of land for applications such as homeland security and critical infrastructure protection. When WSNs are used as barriers, they are typically deployed for extended period of time, so it is of great importance that the network has a long lifetime. Sensors are highly constrained in their energy usage, even when deploying the current energy-harvesting technology. It is necessary that the harvested energy be used effectively. The lifetime problem for WSNs with no energy harvesting has been studied extensively. In this paper, we study lifetime issues of the k-barrier coverage problem for energy harvesting WSNs. First we develop an algorithm that finds a repeating sleep/wakeup schedule that can provide the perpetual operation of the maximum number of barriers in an energy harvesting WSN. Then in the case that perpetual operation can not be achieved, we give an exact solution to the problem of achieving maximum lifetime for the application of k-barrier coverage in energy harvesting WSNs.

Achieving location error tolerant barrier coverage for wireless sensor networks

Barrier coverage is a critical issue in wireless sensor networks deployed in security applications (e.g., border protection), whose performance strongly depends on the locations of sensor nodes. Existing works on barrier coverage typically assume that sensor nodes have accurate location information, which is not reasonable or practical for many real sensor networks. In this paper, we study the barrier coverage problem when sensor nodes have location errors and deploy mobile sensor nodes to improve barrier coverage if the network is not barrier-covered after initial deployment. We analyze the effects of location errors for barrier coverage and propose a fault-tolerant weighted barrier graph to model the barrier coverage formation problem. Based on the graph, we prove that the minimum number of mobile sensor nodes needed to achieve barrier coverage with a guarantee is the length of the shortest path on the graph. Furthermore, we improve the computational efficiency of the fault-tolerant barrier coverage formation algorithm by removing unnecessary edges on the graph. Experimental results validate the correctness of our analysis and the proposed algorithms.

MobiBar: An autonomous deployment algorithm for barrier coverage with mobile sensors

Critical homeland security applications, such as international border surveillance and zone monitoring in case of biological attacks, require the timely creation of a barrier of sensors along the border to be monitored. Mobile Wireless Sensor Networks have the potential to meet the desired coverage requirements, by exploiting the device coordination and self-deployment capabilities. However the design of effective and efficient algorithms is challenging. In this paper we propose MobiBar, an autonomous deployment algorithm for k-barrier coverage with mobile sensors. MobiBar coordinates sensor movements in order to construct k distinct complete barriers and to ensure the desired level of redundancy. We formally prove that MobiBar terminates in a finite time and that the final deployment provides the maximum level of barrier coverage with the available sensors. Furthermore, we show that MobiBar is able to self-reconfigure and self-heal the network to deal with dynamic coverage requirements and sudden sensor failures. We study the performance of MobiBar by means of simulations. Results show that it achieves performance close to centralized solutions and it outperforms recent distributed approaches with respect to several performance metrics.

Adaptive Barrier Coverage Using Software Defined Sensor Networks

This paper investigates the adaptive barrier coverage system in wireless sensor networks, where multiple mobile sensor nodes collaboratively move based on cloud computing. This system aims to adaptively maintain a barrier coverage surrounding a dynamic zone, such as nuclear leakage area and toxic gas area. Since such a zone is usually dangerous and invisible, it is necessary to monitor and track its boundary for detecting unwanted people nearby and warning them. Existing studies on mobile barrier coverage mainly focus on static zones, which cannot directly apply into dynamic zones because their movement strategies are not flexible with dynamics. To address such a problem, we propose a novel adaptive barrier coverage system. The challenge is to effectively maintain the barrier when the change of dynamic zone is unpredictable. The proposed system leverages the software defined concept, in which the mobile sensor nodes execute the local sensing tasks and the cloud computes the real-time optimal strategy to control the movements of nodes. Extensive simulations based on large-scale real trace demonstrate the efficiency and the efficacy of the proposed system.